There are plenty of storage and processing demands for discrete data in Internet applications. These data possess both logic discreteness and time discreteness features. Traditional business-based data processing method are inefficient and closed. Thereby industry gradually turns to use big data technology to satisfy the reading, writing, and processing demand for such discrete data, which improves performance and extensibility. In consideration of performance and operability, however, big data decreases the demand for data consistency in some degree. Therefore, discrete nodes in network need discrete data hold by separate nodes to form public sharing data and require the data to meet the demand for public consistency on verification logic (e.g. distributed multiple nodes respectively maintain a group of discrete transaction data at the same time and keep global consistency for transactions according to the needs; After multiple processing nodes discretely receive or generate a group of input data respectively, it coordinates to generate a group of publicly recognized consistent data etc.), it should be conducted according to some specific arbitration and coordination mechanism. Current arbitration method includes: central server arbitration, agent node arbitration, and weighted node arbitration.
The above arbitration methods are centralized or quasi-centralized coordinated methods. They need to set and run a group of centralized nodes/semi-centralized nodes. Other nodes register on the node group and use centralized coordination and arbitration mechanism to assemble data and establish consistent verification relation for the data. This is the most regular processing method which distributed computing applies to public sharing data on consistency.
In addition, there are algorithms using POW (power of work) to coordinate node assembling behavior, namely, a POW arbitration method. This method is used in a totally decentralized computing environment.
Above all, in current computing network, the use of centralized arbitration mechanism decrease the parallel feature of the whole system and increase the risk of single point failures. At the same time, the centralized nodes, because of their importance, often become the subject of network attacks and hijacks. Furthermore, centralized arbitration methods are not suitable for decentralized computing scenarios. Moreover, the current POW arbitration method decentralized applications consume a lot of computing resources and suffers from low arbitration efficiency.